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跨多重慢性疾病差异研究联盟的双向数据协调:机会和挑战的管道描述

Hyelee Kim1, Shuang Liang2, Kathy Lanier2

  • 1Department of Epidemiology and Biostatistics, University of California, San Francisco (UCSF), USA; Research Coordinating Center to Reduce Disparities in Multiple Chronic Diseases, UCSF, USA; Division of Preventive Science, Department of Medicine, UCSF, USA; Computational Precision Health, University of California, Berkeley, and UCSF, USA.

Journal of biomedical informatics
|March 2, 2026
PubMed
概括

本研究概述了研究健康的社会决定因素的大型研究联盟的双向数据协调管道. 它解决了不同人群的数据集成挑战,并利用大型语言模型提高效率.

关键词:
共同的数据元素数据统一和数据协调.健康差异 在健康方面存在差异.大型语言模型.有多种慢性疾病.健康的社会决定因素

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